Non-transitory computer-readable recording medium, estimation method, and estimation device

Abstract

A non-transitory computer-readable recording medium having stored therein a program causes a computer to execute a process. The process includes acquiring first information related to a linear circuit having a plurality of ports for receiving or outputting a high frequency signal, and second information related to a frequency of the high frequency signal, estimating an S-parameter for two ports of the plurality of ports at the frequency, based on a learned model, and when the second information indicates that the frequency is 0 Hz and the estimated S-parameter is out of a range, restricting the S-parameter to be within the range. The learned model is generated by performing machine learning on a plurality of pieces of training data. The plurality of pieces of training data defines a relationship among a plurality of pieces of first information of the linear circuit, a plurality of frequencies, and a plurality of S-parameters.

1 . A non-transitory computer-readable recording medium having stored therein a program for causing a computer to execute a process, the process comprising:
 acquiring first information related to a linear circuit having a plurality of ports for receiving or outputting a high frequency signal, and second information related to a frequency of the high frequency signal;   estimating an S-parameter for two ports of the plurality of ports at the frequency, based on a learned model from the first information and the second information; and   when the second information indicates that the frequency is 0 Hz and the estimated S-parameter is out of a range, restricting the S-parameter to be within the range, wherein   the learned model is generated by performing machine learning on a plurality of pieces of training data, the plurality of pieces of training data defining a relationship among a plurality of pieces of first information of the linear circuit, a plurality of frequencies, and a plurality of S-parameters calculated for a corresponding one of the plurality of pieces of first information and a corresponding one of the plurality of frequencies.   
     
     
         2 . The non-transitory computer-readable recording medium according to  claim 1 ,
 wherein the restricting never restricts the estimated S-parameter when the second information indicates that the frequency is other than 0 Hz.   
     
     
         3 . The non-transitory computer-readable recording medium according to  claim 1 , wherein
 when the estimated S-parameter is larger than a first maximum value of the range, the restricting sets the S-parameter to the first maximum value, and   when the estimated S-parameter is smaller than a first minimum value of the range, the restricting sets the S-parameter to the first minimum value.   
     
     
         4 . The non-transitory computer-readable recording medium according to  claim 1 , wherein
 each of the plurality of S-parameters in the plurality of pieces of training data is normalized by a second maximum value and a second minimum value,   the second maximum value is larger than a maximum value of the range, and   the second minimum value is smaller than a minimum value of the range.   
     
     
         5 . The non-transitory computer-readable recording medium according to  claim 4 , wherein the estimating estimates the S-parameter by decoding, based on the second maximum value and the second minimum value, a value generated based on the learned model. 
     
     
         6 . The non-transitory computer-readable recording medium according to  claim 1 , wherein
 the restricting restricts the S-parameter to be within the range when the two ports are opened or short-circuited, and   the restricting never restricts the S-parameter when the two ports are not opened or short-circuited.   
     
     
         7 . The non-transitory computer-readable recording medium according to  claim 6 , wherein when the two ports are port  1  and port  2 , the S-parameter is S 21 . 
     
     
         8 . An estimation method comprising:
 acquiring first information related to a linear circuit having a plurality of ports for receiving or outputting a high frequency signal, and second information related to a frequency of the high frequency signal;   estimating an S-parameter for two ports of the plurality of ports at the frequency, based on a learned model from the first information and the second information; and   when the second information indicates that the frequency is 0 Hz and the estimated S-parameter is out of a range, restricting the S-parameter to be within the range, wherein   the learned model is generated by performing machine learning on a plurality of pieces of training data, the plurality of pieces of training data defining a relationship among a plurality of pieces of first information of the linear circuit, a plurality of frequencies, and a plurality of S-parameters calculated for a corresponding one of the plurality of pieces of first information and a corresponding one of the plurality of frequencies.   
     
     
         9 . An estimation device comprising:
 an acquirer that acquires first information related to a linear circuit having a plurality of ports for receiving or outputting a high frequency signal, and second information related to a frequency of the high frequency signal;   an estimator that estimates an S-parameter for two ports of the plurality of ports at the frequency, based on a learned model from the first information and the second information; and   a restrictor that, when the second information indicates that the frequency is 0 Hz and the estimated S-parameter is out of a range, restricts the S-parameter to be within the range, wherein   the learned model is generated by performing machine learning on a plurality of pieces of training data, the plurality of pieces of training data defining a relationship among a plurality of pieces of first information of the linear circuit, a plurality of frequencies, and a plurality of S-parameters calculated for a corresponding one of the plurality of pieces of first information and a corresponding one of the plurality of frequencies.